1. Field of the Invention
The present invention relates to a digital fuzzy inference system.
The fuzzy theory was suggested by L. A. Zadeh, Professor at California State University, in 1965, and the possibility of practical use of the theory was proven by E. H. Mamdani, Professor at the University of London, in 1974. Various means of implementing the theory have been proposed afterward. There are the following typical examples of such means. In European Patent Application No. 0 092 832 (Japanese Patent Disclosure No. 58-192407), there is described an operation control system for vehicles which lessens the frequency of notch-changes to obtain comfortable ride by inference using software. U.S. Pat. No. 4,716,540 (Japanese Patent Disclosure No. 61-20428) discloses analog fuzzy logic circuits implemented by current circuits. Furthermore, in Nikkei Electronics, No. 457, Oct. 3, 1988, there are described processors using memories developed at Hosei University, North Carolina State University and so on, and processors dedicated to fuzzy controllers for writing data for inference into instruction memories, which are developed at Togai Infralogic Company (Masaki Togai and Hiroyuki Watanabe of AT&T Bell Laboratories, "Expert System on a Chip: An Engine for Real-Time Approximate Reasoning", IEEE EXPERT, FALL 1986) and so on.
The conventional fuzzy inference systems have the following drawbacks. The system based on software can be implemented for the time being by means of a personal computer, microcomputer or the like, but it is very slow in inference speed and thus not practical. The analog system using current circuits requires an interface for use in cooperation with a digital computer. The system using memories and a dedicated processor system require large-scale development tools and system clocks because of the use of memories. In order to increase the inference speed it requires faster clocks. The system clocks may generate noise where the system is used in neighboring analog circuits.
Furthermore, the result of inference depends on how to define an if-part (or condition part) membership function and, more particularly, its form or type. With the conventional systems, it is difficult to freely define the form or type of the if-part membership function. Similarly, it is impossible to freely define then-part (or conclusion part) membership functions because their output positions or addresses are fixed to predetermined discrete values and they are also defined uniquely.